Schedule

Week 1

Tuesday – 28 August

• Intro to Course < 30 min.
  • avatar name
• Intro to Machine Learning 45 minutes
• Homework. Teams prepare to define and give examples of:
  • How to transpose a matrix 
  • How to compute a dot product.
  • What is the definition of the inverse of a matrix and how to compute the inverse of a 2 x 2 matrix.
• Homework. read Chapter 1. 

Thursday – 30 August

• Quiz (socrative.com)
• Discussion of Homework  (30 minutes)
• Introduction to Python Notebooks  (45 minutes)
• Optional notebooks that may be helpful
  • getting started with Numpy
  • getting started with Pandas
  • Random Friday

Week 2

Tuesday – 4 September

• Introduction to Chapter 2
• Homework. read Chapter 2.

Thursday – 6 September

• Quiz
• lab 1 due Happiness
  • All these assignments can be done with a partner.
  • They can be done using a Python notebook or just using a Python code file that you execute from the command line
  • You will demo the code to me in class. In addition, you need to give me a 3×5 index card with
    • the name of the assignment
    • the names of the partners
    • the demo date

Week 3

Tuesday – 11 September

• Quiz chapter 2
• Correlation
• lab 0: Correlation Lab
• Regression  (2 weeks)

Thursday – 13 September

Week 4

Tuesday – 18 September

• Quiz chapters 3 and 4

Thursday – 20 September

• lab 2 due: Housing

Week 5

Tuesday – 25 September

• Introduction to Decision Trees

Thursday – 27 September

• Decision Trees Continued

Week 6

Tuesday – 2 October

• lab 3: Decision Trees
• Quiz chapter 6 and lectures

Thursday – 4 October

• lab 3 due: Decision Trees

Week 7

Tuesday – 9 October

• Ensemble Methods Random Forests, Boosting (3 weeks)
• Bagging Predictors
• Pasting

Thursday – 11 October

• XGBoost
  • XGBoost: A Scalable Tree Boosting System
  • XGBoost documentation from its github repo.
• lab 4 due: XGBoost
• lab 5: Analyzing Text

Week 8

Tuesday – 16 October

 

Thursday – 18 October

• Quiz: XGBoost ch 7
• PCA Dimension Reduction

Week 9

Tuesday – 23 October

• Deep Learning (3-4 weeks)

Thursday – 25 October

Week 10

Tuesday – 30 October

• Introduction to Deep Learning using Keras
• Google Colab
• Deep Learning Lab 1

Thursday – 1 November

•  Quiz – PCA & Deep Learning (ch  8, 10, parts of 11 + lecture)

Week 11

Tuesday – 6 November

Thursday – 8 November

Week 12

Tuesday – 13 November

• Quiz – CNN (ch 13 + lecture)

Thursday – 15 November

Week 13

Tuesday – 20 November

• Word Embeddings Notebook

Thursday – 22 November

Week 14

Tuesday – 27 November

• Introduction to Unsupervised Learning: Clustering
  • Dog Breeds Google Doc
  • Dog Breeds Sorted

Thursday – 29 November

• Reinforcement Learning

Week 15

Tuesday – 4 December

Thursday – 6 December